CS 3361 - Artificial Intelligence

Autumn 1997
Section A: Ashok Goel
Section B: Todd Griffith

Meeting Place: College of Computing 101
Meeting Times:

• Section A: 1:05 to 1:55 pm on Mondays, Wednesdays, and Fridays
  
• Section B: 2:05 to 2:55 pm on Mondays, Wednesdays, and Fridays
  

Prerequisites: CS 2360 - Knowledge Representation and Processing

Instructor (Section A): Ashok K. Goel
Bail: goel@cc.gatech.edu
Phone: 894-8994
Office: 243, College of Computing Building
Office Hours: 1:05 to 2:00 pm on Mondays, Wednesdays, Thursdays and Fridays
Instructor (Section B): Todd W. Griffith
Bail: griffith@cc.gatech.edu
Phone: 894-6710
Office: College of Computing Building - TA area
Office Hours: 3:00 to 4:30pm on Mondays, 1:00 to 2:30pm Thursdays.
Office Policy: I am likely to be at the CoC only during my office hours. The best way to contact me is by email.

Teaching Assistants: Yaxin Liu (section A), Sunil Mishra (section B),
Email: yxliu@cc.gatech.edu, smishra@cc.gatech.edu
Yaxin's Office: CoC Building Rm. 153.
Yazin's Office Hours: 1:00-2:30pm Tuesdays and Thursdays
Sunil's Office: CoC Building TA area
Sunil's Office Hours: 2:30-4:00pm Tuesdays and Thursdays

Description

CS 3361 is a 4-credit undergraduate-level introductory course on Artificial Intelligence (AI). The course will cover basic AI concepts such as search, knowledge, representation, memory, inference, and control. In addition, it will cover selected topics in advanced areas such as problem solving, understanding, and learning.

Objectives

The main objectives of the course are (i) to provide a basic survey of AI, (ii) to develop a conceptual understanding of the basic issues and major topics in AI, and (iii) to develop design skills for building simple AI systems.

Format

The course will consist of class lectures and discussions, discussions on the <git.cc.class.3361> newsgroup, reading assignments, homework assignments, four design projects, and three examinations. Class notes will be posted on the newsgroup <git.cc.class.3361> and on a class web page. Class participation too will be important and is strongly encouraged.

Reading Assignments

• All reading assignments will be from: Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig, Prentice Hall, 1995. This is the required text. See the course schedule for the schedule of expected readings.
• Supplemental AI texts: Artificial Intelligence: E. Rich and K. Knight, McGraw-Hill, Second Edition; Artificial Intelligence, P. Winston, Addison-Wesley, Third Edition;Artificial Intelligence, E. Charniak and D. McDermott, Addison-Wesley.
• Supplemental AI programming texts:Lisp, Winston and Horn, Addison-Wesley;AI Programming, Charniak, Riesbeck, McDermott and Meehan, Lawrence Erlbaum;Paradigms of AI Programming, P. Norvig, Morgan-Kauffman.

Projects

Each of the four design projects will be about two weeks long. Familiarity with Common Lisp will be assumed. Students will work on these projects in small rotating groups. Please note that all projects must be turned in on time. No extensions will be granted but incomplete projects will be graded for partial credit.

Examinations

There will be two short mid-term examinations and a longer final examination.

Grades

The first mid-term examination will constitute 10%, the second mid-term examination will constitute 15%, and the final examination will constitute 30% of the grade. Each design project will count for 10% of the grade. Class attendance and participation will count for the remaining 5%. The raw scores will be normalized and the final grades will be based on the normalized scores.

Course Schedule

Please check the course schedule for the class. It may be updated on occassion.

Assignments

• Here is assignment #1 it consists of an assignment specification and a map in GIF form.
• Here is assignment #2
• Here is assignment #3
• Here is assignment #4

Course Notes

• September 26, 1997 Introduction to Artificial Intelligence
• September 29, 1997 Agents
• October 3, 1997 Problem Solving (REVISED 10/9)
• October 6 & 8, 1997 Planning
• October 10, 1997 Rule-Based Problem Solving
• October 13, 1997 Case-Based Problem Solving
• October 20-22, 1997 Learning
• October 24, 1997 Connectionism
• October 31, 1997 Low-Level Vision
• November 3, 1997 Vision Understanding
• November 7, 1997 Natural Language Syntax
• November 7, 1997 Natural Language Semantics
• November 10, 1997 Natural Language Pragmatics

Sample Exams

• From Winter 97: Exam 1 & Exam 2

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